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Variable-Rate Nitrogen Management Creates Opportunities and Challenges for Corn Producers Thomas A. Doerge, Global Agronomy and Nutritional Sciences, Pioneer Hi-Bred, a DuPont Company, Des Moines, IA 50306-3454 Corresponding author: Thomas A. Doerge. Tom.Doerge@Pioneer.com
Abstract Adoption of variable-rate N management by North American corn (Zea mays L.) producers is low, despite the potential economic and environmental benefits of this practice. A major obstacle is that recommended N fertilizer rates based on yield goal are often poorly correlated with actual economically optimum N rates. Nitrogen response patterns are often field- and season-specific and can vary widely within the same field, further complicating adoption. Side-by-side comparisons of uniform- and variable-rate N management have revealed no consistent advantages for either strategy in yields achieved, profitability, whole-field N usage, or N-use efficiency by plants. In the future, a better understanding of temporal variation in N soil test levels, better crop simulation models, and improved N sensing and application equipment may assist growers in capturing the benefits of site-specific N management. Will Variable-Rate N Work for Corn? Every season, corn producers must decide on the correct amount of nitrogen (N) fertilizer to apply to their fields. Today’s GPS-enabled application equipment and related precision farming tools have created another decision for growers: whether to apply N at a uniform rate or at variable rates within fields. Early variable-rate management success with N in sugarbeet (Beta vulgaris L.) (8) has prompted some growers to consider site-specific N management for corn production. Tailoring N application rates to more exactly meet crop needs should increase profitability, reduce environmental risk, and may result in higher and more consistent grain quality. However, adoption rates for variable N application have lagged behind those of other precision farming practices. Recent university research has revealed why: managing N in sub-regions of fields or even in whole fields is a complex process, and challenges some long-held nutrient management beliefs. The key to success and eventual adoption of variable-rate N management will be the development of decision-making criteria that can accurately predict N rates for sub-regions of corn fields that are economically optimum and environmentally sustainable. This review discusses the difficulties in predicting crop N needs, challenges for variable-rate N adopters, and future improvements in site-specific N management for corn production in North America. Can We Accurately Predict N Rates for Corn? The Nitrogen Cycle in Soils. The availability of N to crop plants is affected by a complex set of interacting soil, biological, climatic, and management factors (Fig. 1). These factors have been studied extensively over the last century and this understanding has been used to develop and refine methods for determining the N fertilizer requirements of many crops. In principle, the predicted N requirement is the difference between the N needed to produce the biomass of the crop and the net supply of N to the plants from all other sources.
Using ‘Yield Goal’ to Determine N Fertilizer Rates. Agronomists have long sought a simple, easy-to-use algorithm or formula to calculate economically optimum N fertilizer rates (EONR). The typical practice in many states is to use the common-sense relationship between the expected crop yield and the amount of N the crop will need. This relationship implies that high-yielding locations will respond to higher rates of N while low-yielding locations should require less N. Most recommendation strategies include some adjustment for the amount of N needed per bushel of yield, plant uptake efficiency and any applicable N credits. A typical example is the formula used in many areas of the Midwest (15): N recommendation = target yield X 1.2 - N credits In this example, the target yield is the average yield achieved in the field over the past five years plus five percent. Each bushel of grain yield is assumed to require 1.2 lb of N and N credits include additions of N in legume residues, starter and other fertilizers, manures, herbicide carrier N solutions, and irrigation water. For a 150-bu/acre corn crop following soybeans [Glycine max (L.) Merr.] (N credit of 40 lb/acre) the calculated N recommendation would be 140 lb/acre. Other states have modified their N recommendation algorithms to include other factors that are locally important. These include soil nitrate and organic matter levels (14), soil type and landscape position (17), and user-defined management zones (12). Yield Goals are Poorly Related to Optimum N Rates. Without question, the total amount of N utilized by a corn crop will increase with yield level. However, extensive research has shown that expected, potential, average, or even actual yields are often very poorly correlated with the economically optimum N rate for a site. Across more than 460 field studies in Ontario, Colorado, Illinois, Iowa, Michigan, Minnesota, and Wisconsin, variation in the recommended N rate explained less than 10% of the variation in the actual economically optimum N rate (4,9,10,12,13,16,23). Other important findings have emerged from these studies: • The EONRs in sub-regions of a single field varied widely, ranging from < 30 to > 200 lb of N per acre. • High-yielding sites with low N requirements and low-yielding sites that responded to unexpectedly high rates of N were common. • The best predictor of EONR was the yield of control plots that received no N fertilizer. Unfortunately this information is not available to guide pre- or in-season N management. • Soil type, landscape position, and soil drainage class showed no consistent relationship with N response. • Nitrogen response patterns in fields with similar cropping history, yield levels, and soil characteristics can be very dissimilar. • Nitrogen response patterns in the same field varied dramatically in different seasons even if the overall yield patterns were similar across years. In summary, there are temporal factors affecting the N levels in soils that are independent of soil type and landscape position that are not well understood and complicate variable-rate N management. Current Variable-Rate N Strategies In the mid-1990s, many researchers expected that developing accurate N recommendations for sub-regions of fields would be a certainty. Part of this optimism stemmed from the development of many new tools to routinely measure site characteristics that directly affected crop N status, soil N supply, or crop productivity. These included pre-season (6) and late-spring soil nitrate tests (2), late-season stalk nitrate tests (3), remote sensing of crop and soil properties (5), site-specific data from yield monitors (17), and soil electrical conductivity maps (18). However, for these new spatial tools to be effective, the variable N application maps they helped produce had to be accurate and applicable from year-to-year. Proactive Strategies. The first variable-rate N strategies took a proactive, prescriptive approach. Fields were divided into smaller sub-regions and methods developed for whole-field N management were applied to these individual “management zones”. The variable N rate prescription map was developed prior to the growing season and fertilizer was applied at the usual time(s). These approaches included the use of grid soil sampling (11) and crop productivity zones (12,17). In general, many studies found: • There is no consistent income advantage for either variable- or uniform-rate N strategies. • Yields were not impacted by N strategy. • Whole-field N rates were similar for either strategy. • Post-season soil nitrate levels were not appreciably reduced when using variable-rate N. • Either strategy could out-perform the other in a particular growing season, depending on crop-related conditions. Other difficulties were revealed through detailed on-farm research over the past ten years in Minnesota (7,9). This research found that N response patterns within a field often do not mimic yield patterns. This could invalidate yield level indicators such as yield maps, remotely-sensed estimations of crop biomass, and corn suitability ratings for use as sources of information on which to base site-specific N recommendations. This research also discovered that N response patterns within the same field can be dissimilar in different seasons (Fig. 2). Clearly, much additional research is needed to be able to predict N response patterns on a field scale.
Reactive Strategies. A second approach to site-specific N management involves reacting to actual N levels in corn fields during the growing season. Crop N status is monitored in near-real time and N is applied only when and where it is needed. With this method, plant or canopy reflectance of light or chlorophyll content is used to indicate plant N stress. This approach can utilize remotely-sensed crop canopy imagery and typically requires the presence of an adequately N-fertilized “reference strip” within each field (20). Interestingly, these optical methods create in-season N prescription maps that are based on crop N stress rather than predicted yield levels. A variation of this method is to equip field applicators with remote sensing devices similar to those contained in satellites or aircraft. Then, the applicator moves through the field, sensing the N status of the crop and directing N application on-the-go (Fig. 3). For example, Scharf and Lory (19) developed a calibration between corn color measured in aerial photographs at the V6-V7 stage and sidedress N need. These crop color readings are compared to similar readings from a well-fertilized reference strip to determine the presence and severity of N stress. From that estimation, it may be possible to predict optimum sidedress N rates.
Challenges for Variable-Rate N Adopters Although technology is available to deliver different rates of N across variable fields, this practice is not yet economically beneficial in most cases. Growers who wish to implement variable-rate N management strategies should be aware of these challenges: • Potential cost savings can be minimal. The maximum potential benefit of a variable N strategy vs. a conventional uniform-rate N strategy is typically between 5 and 15 US$/acre. When all the costs of developing and executing the variable-rate strategy are considered, the net return may be insufficient to cover the added expenses. • Prescriptive N strategies involve risk. Prescriptive strategies are not yet reliable and cannot respond to unexpected in-season crop conditions. These could include unusually favorable growing conditions or yield-limiting events such as frost, hail, stalk lodging, pest infestation, drought or N losses resulting from excessive rainfall and denitrification . • Reactive N strategies can limit yield potential. Nitrogen deficiencies prior to the 8-leaf stage can result in non-recoverable yield loss (1). In addition, adverse weather conditions after emergence could restrict field entry and further delay the correction of an early-season N deficiency. • Check strips should be included. If a variable-rate N strategy is used, growers should be sure to include several uniform-rate check strips per field. These strips can be conveniently harvested as separate loads on a yield monitor or as side-by-side comparisons with a weigh wagon. A uniform N rate should be used in these check strips based on current university or local recommendations. Variable-Rate N Considerations for the Future New N management strategies will be adopted by producers if they reduce risk and are affordable, accurate, easy-to-use, and environmentally sustainable. For corn production, this probably precludes the use of grid soil sampling for N content, due to the cost of sampling and analysis and the limited life of sample results. Future use of any N recommendation formula based on yield goal, productivity index, or soil type should be carefully evaluated for accuracy and reliability under field conditions. Clearly there is a need for new diagnostic tools that provide a better prediction of the EONR in sub-regions of fields. These tools must consider temporal variability in the environmental factors that affect crop responsiveness to N. For example, scientists at Oklahoma State University have developed a successful variable-rate N algorithm and application system for use in winter wheat (Triticum aestivum L.). The researchers are currently modifying this system for use with corn (22). Crop simulation models may someday provide an economical way to estimate economic and environmental outcomes of different N management. These models intensively characterize a site and then evaluate crop growth and nutrient utilization with historical weather data. Initial model simulations have shown only small benefits for variable-rate N management strategies (21). One excellent contribution of these models is the identification of site characteristics that do and do not have significant effects on crop response to N fertilizer in different cropping regions. However, these models will only add value at the farm level if they lead to a better understanding of the way corn crops respond to N fertilizer. The technology available to vary N fertilizer rates within a field likely exceeds the knowledge of how to best use it. When finally successful, variable-rate N strategies will need to be carefully customized to fit local soil, climatic, environmental and agronomic conditions. Literature Cited 1. Binder, D. L., Sander, D. H., and Walters, D. T. 2000. Maize response to time of nitrogen application as affected by level of nitrogen deficiency. Agron. J. 92:1228-1236. 2. Binford, G. D., Blackmer, A. M., and Cerrato, M. E. 1992. Relationships between corn yields and soil nitrate in late spring. Agron. J. 84:53-59. 3. Binford, G. D., Blackmer, A. M., and Meese, B. G. 1992. Optimal concentrations of nitrate in corn stalks at maturity. Agron. J. 84:881-887. 4. Blackmer, A. M., Morris, T. F., and Binford, G. D. 1992. Predicting N fertilizer needs for corn in humid regions: Advances in Iowa. Page 359 in: Predicting N fertilizer needs for corn in humid regions, Bull. Y-226. B. R. Bock and K. R. Kelley, eds. National Fertilizer and Environ. Res. Center, Tennessee Valley Authority, Mussel Shoals, AL. 5. Blackmer, T. M., Schepers, J. S., Varvel, G. E., and Walter-Shea, E. A. 1996. Nitrogen deficiency detection using reflected shortwave radiation from irrigated corn canopies. Agron. J. 88:1-5. 6. Bock, B. R., and Hergert, G. W. 1991. Fertilizer nitrogen management. Pages 139-164 in: Managing nitrogen for groundwater quality and farm profitability. R. F. Follett, D. R. Keeney, and R. M. Cruse, eds. Soil Science Society of America, Madison, WI. 7. Braum, S. M., Hinds, P., Malzer, G. L., Bell, J., Mulla, D., and Robert, P. C. 1999. Terrain attributes and soil nitrogen: Spatial effects on corn yield responses to nitrogen fertilization for a northern, glaciated landscape. Pages 195-201 in: Proc. of the Fourth International Conf. on Precision Agric. P. C. Robert, ed. ASA-CSSA-SSSA, Madison, WI. 8. Cattanach, A., Franzen, D., and Smith, L. 1996. Grid soil testing and variable-rate fertilizer application effects on sugarbeet yield and quality. Pages 1033-1038 in: P. C. Robert, R. H. Rust and W. E. Larson, eds. Proc. of the 3rd International Conf. on Precision Agric. ASA-CSSA-SSSA, Madison, WI. 9. Davis, J. G., Malzer, G. L., Copeland, P. J., Lamb, J. A., and Robert, P. C. 1996. Using yield variability to characterize spatial crop response to applied N. Pages 513-519 in: P. C. Robert, R. H. Rust, and W. E. Larson, eds. Proc. of the 3rd International Conf. on Precision Agric. ASA-CSSA-SSSA, Madison, WI. 10. Everett, M. W., and Pierce, F. J. 1996. Variability of corn yield and soil profile nitrates in relation to site-specific N management. Pages 43-53 in: Proc. of the 3rd International Conf. on Precision Agric. P. C. Robert, R. H. Rust, and W. E. Larson, eds. ASA-CSSA-SSSA, Madison, WI. 11. Ferguson, R. B., Hergert, G. W., and Schepers, J. S. 1997. Strategies for site-specific nitrogen management. Pages 387-395 in: Precision Agric. 97: Proc. of the 1st European Conf. on Precision Agric. J. V. Stafford, ed. Bios Scientific Publ., Oxford, England. 12. Fleming, K. 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Pages 425-432 in: Proc. of the 3rd International Conf. on Precision Agric. P. C. Robert, R. H. Rust, and W. E. Larson, eds. ASA-CSSA-SSSA, Madison, WI. 17. Kitchen, N. R., Hughes, D. F., Sudduth, K. A., and Birrell, S. J. 1995. Comparison of variable rate to single rate nitrogen fertilization application: Corn production and residual soil NO3-N. Pages 427-442 in: Proc. of the 2nd International Conf. on Precision Agric. P. C. Robert, R. H. Rust, and W. E. Larson, eds. ASA-CSSA-SSSA, Madison, WI. 18. Lund, E. D., Christy, C. D., and Drummond, P. E. 1999. Practical applications of soil electrical conductivity mapping. Pages 771-779 in: Precision Agric. 99: Proc. of the 2nd European Conf. on Precision Agric. Soc. of Chemical Industry. J. V. Stafford, ed. Sheffield Academic Press, Ltd., UK. 19. Scharf, P. C., and Lory, J. A. 2002. Calibrating corn color from aerial photographs to predict sidedress nitrogen need. Agron. J. 94:397-404. 20. Schepers, J. S., Francis, D. D., Virgil, M. F., and Below, F. E. 1992. Comparisons of corn leaf nitrogen and chlorophyll meter readings. Commum. Soil Sci. Plant Anal. 23:2173-2187. 21. Sogbedji, J. M., van Es, H. M., Klausner, S. D., Bouldin, D. R., and Cox, W. J. 2001. Spatial and temporal processes affecting nitrogen availability at the landscape scale. Soil and Tillage Res. 58:233-244. 22. Solie, J. B., Stone, M. L., Needham, D. E., Washmon, C. N., Raun W. R., Johnson, G. V., Lukina, E. V., and Thomason, W. E. 2000. In-season N fertilization using an in-season estimate of potential yield. Proc. of the 5th International Conf. on Precision Agric. ASA-CSSA-SSSA, Madison WI. 23. Vanotti, M. B., and Bundy, L. G. 1994. An alternative rationale for corn nitrogen fertilizer recommendations. J. Prod. Agric. 7:243-249. |
